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DBMS > EXASOL vs. GridDB vs. Kdb vs. SiteWhere vs. Spark SQL

System Properties Comparison EXASOL vs. GridDB vs. Kdb vs. SiteWhere vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGridDB  Xexclude from comparisonKdb  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Scalable in-memory time series database optimized for IoT and Big DataHigh performance Time Series DBMSM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSTime Series DBMS
Vector DBMS
Time Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comgriddb.netkx.comgithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesdocs.griddb.netcode.kx.comsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolToshiba CorporationKx Systems, a division of First Derivatives plcSiteWhereApache Software Foundation
Initial release200020132000 infokdb was released 2000, kdb+ in 200320102014
Current release5.1, August 20223.6, May 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree 32-bit versionOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++qJavaScala
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyespredefined schemeyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesnono
Secondary indexesyesyesyes infotable attribute 'grouped'nono
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (q)noSQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
HTTP RESTJDBC
ODBC
Supported programming languagesJava
Lua
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsno
Triggersyesyesyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users can be defined per databaserights management via user accountsUsers with fine-grained authorization conceptno
More information provided by the system vendor
EXASOLGridDBKdbSiteWhereSpark SQL
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Integrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
tick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricsGitHub trending repository
» more
kdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
upon request
» more

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More resources
EXASOLGridDBKdbSiteWhereSpark SQL
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